Differential phospho/protein analysis - CRC Batch 1
Sophie Herbst
Analysis date: 2023-02-10
Depends on
DIPG_FirstBatch_DataProcessing Script
load("../Data/Cache/Xenografts_Batch1_2_DataProcessing.RData")TODO
- Do differential abudance analysis for prep batch and mass spec run
Setup
Load libraries and functions
Analysis
DEP
Tyrosine all
Each condition vs ctrl
data_diff_ctrl_vs_E_pY <- test_diff(pY_se_Set1, type="manual", test = "E_vs_ctrl")## Tested contrasts: E_vs_ctrldep_ctrl_vs_E_pY <- add_rejections_SH(data_diff_ctrl_vs_E_pY, alpha = 0.05, lfc = log2(1.2))
GGPlotly_Volcano(dep_ctrl_vs_E_pY, contrast = "E_vs_ctrl",
add_names = TRUE,
additional_title = "pY") ## Warning: `gather_()` was deprecated in tidyr 1.2.0.
## ℹ Please use `gather()` instead.
## ℹ The deprecated feature was likely used in the plotly package.
## Please report the issue at <]8;;https://github.com/plotly/plotly.R/issueshttps://github.com/plotly/plotly.R/issues]8;;>.Return_DEP_Hits_Plots(data = pY_Set1_form, dep_ctrl_vs_E_pY, comparison = "E_vs_ctrl_diff")## Warning: Using an external vector in selections was deprecated in tidyselect 1.1.0.
## ℹ Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(comparison)
##
## # Now:
## data %>% select(all_of(comparison))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.## 'select()' returned 1:1 mapping between keys and columns## Loading required namespace: reactome.db## 'select()' returned 1:many mapping between keys and columns## 'select()' returned 1:1 mapping between keys and columns
## pathway pval
## 1: A tetrasaccharide linker sequence is required for GAG synthesis 0.3219316
## 2: ABC transporter disorders 0.3501006
## 3: ABC-family proteins mediated transport 0.3501006
## 4: ADP signalling through P2Y purinoceptor 1 0.2273642
## 5: ALK mutants bind TKIs 0.6953125
## 6: APC/C-mediated degradation of cell cycle proteins 0.9683698
## padj log2err ES NES size leadingEdge
## 1: 0.8702169 0.10473282 0.8430233 1.1431478 1 6385
## 2: 0.8702169 0.09957912 0.8255814 1.1194965 1 5687
## 3: 0.8702169 0.09957912 0.8255814 1.1194965 1 5687
## 4: 0.8702169 0.12814292 0.8895349 1.2062180 1 1432
## 5: 0.9703706 0.06143641 -0.6569767 -0.8823673 1 1213
## 6: 0.9814049 0.05617666 0.3859649 0.6052109 2 5687
## Note: Row-scaling applied for this heatmap
data_diff_EC_vs_ctrl_pY <- test_diff(pY_se_Set1, type="manual", test = "EC_vs_ctrl")## Tested contrasts: EC_vs_ctrldep_EC_vs_ctrl_pY <- add_rejections_SH(data_diff_EC_vs_ctrl_pY, alpha = 0.05, lfc = log2(1.2))
GGPlotly_Volcano(dep_EC_vs_ctrl_pY, contrast = "EC_vs_ctrl",
add_names = TRUE,
additional_title = "pY") Return_DEP_Hits_Plots(data = pY_Set1_form, dep_EC_vs_ctrl_pY, comparison = "EC_vs_ctrl_diff")## 'select()' returned 1:1 mapping between keys and columns## 'select()' returned 1:many mapping between keys and columns## 'select()' returned 1:1 mapping between keys and columns## pathway pval
## 1: A tetrasaccharide linker sequence is required for GAG synthesis 0.6124031
## 2: ABC transporter disorders 0.7926357
## 3: ABC-family proteins mediated transport 0.7926357
## 4: ADP signalling through P2Y purinoceptor 1 0.2984496
## 5: ALK mutants bind TKIs 0.6404040
## 6: APC/C-mediated degradation of cell cycle proteins 0.6906077
## padj log2err ES NES size leadingEdge
## 1: 0.9804885 0.06720651 0.6918605 0.9340944 1 6385
## 2: 0.9804885 0.05490737 0.5813953 0.7849533 1 5687
## 3: 0.9804885 0.05490737 0.5813953 0.7849533 1 5687
## 4: 0.9804885 0.10714024 0.8662791 1.1695804 1 1432
## 5: 0.9804885 0.06705126 -0.6744186 -0.9142164 1 1213
## 6: 0.9804885 0.05896945 -0.5518113 -0.8639961 2 983## Warning in min(screen_pval05_neg[, logFcColStr]): no non-missing arguments to
## min; returning Inf## Warning in min(x): no non-missing arguments to min; returning Inf## Warning in max(x): no non-missing arguments to max; returning -Inf## Warning in min(x): no non-missing arguments to min; returning Inf## Warning in max(x): no non-missing arguments to max; returning -Inf## Warning in min(cs1s, na.rm = TRUE): no non-missing arguments to min; returning
## Inf## Warning in max(cs1s, na.rm = TRUE): no non-missing arguments to max; returning
## -Inf## Warning in min(cs2s, na.rm = TRUE): no non-missing arguments to min; returning
## Inf## Warning in max(cs2s, na.rm = TRUE): no non-missing arguments to max; returning
## -Inf## Warning in min(cs3s, na.rm = TRUE): no non-missing arguments to min; returning
## Inf## Warning in max(cs3s, na.rm = TRUE): no non-missing arguments to max; returning
## -Inf
## Note: Row-scaling applied for this heatmap
Plot_Enrichment_Single_Pathway(dep_EC_vs_ctrl_pY, comparison = "EC_vs_ctrl_diff",
pw = "Epigenetic regulation of gene expression")data_diff_EBC_vs_ctrl_pY <- test_diff(pY_se_Set1, type="manual", test = "EBC_vs_ctrl")## Tested contrasts: EBC_vs_ctrldep_EBC_vs_ctrl_pY <- add_rejections_SH(data_diff_EBC_vs_ctrl_pY, alpha = 0.05, lfc = log2(1.2))
GGPlotly_Volcano(dep_EBC_vs_ctrl_pY, contrast = "EBC_vs_ctrl",
add_names = TRUE,
additional_title = "pY")Return_DEP_Hits_Plots(data = pY_Set1_form, dep_EBC_vs_ctrl_pY, comparison = "EBC_vs_ctrl_diff")## 'select()' returned 1:1 mapping between keys and columns## 'select()' returned 1:many mapping between keys and columns## 'select()' returned 1:1 mapping between keys and columns
## pathway pval
## 1: A tetrasaccharide linker sequence is required for GAG synthesis 0.4151329
## 2: ABC transporter disorders 0.9213052
## 3: ABC-family proteins mediated transport 0.9213052
## 4: ADP signalling through P2Y purinoceptor 1 0.8875256
## 5: ALK mutants bind TKIs 0.2053743
## 6: APC/C-mediated degradation of cell cycle proteins 0.4480409
## padj log2err ES NES size leadingEdge
## 1: 0.9343269 0.09054289 -0.7790698 -1.0625762 1 6385
## 2: 0.9658217 0.04754342 0.5348837 0.7313084 1 5687
## 3: 0.9658217 0.04754342 0.5348837 0.7313084 1 5687
## 4: 0.9658217 0.05216303 -0.5581395 -0.7612486 1 1432
## 5: 0.8935583 0.13214726 0.8779070 1.2002996 1 1213
## 6: 0.9343269 0.07647671 -0.6679829 -1.0309284 2 983
## Note: Row-scaling applied for this heatmap
EC vs E
data_diff_EC_vs_E_pY <- test_diff(pY_se_Set1, type = "manual",
test = c("EC_vs_E"))## Tested contrasts: EC_vs_Edep_EC_vs_E_pY <- add_rejections_SH(data_diff_EC_vs_E_pY, alpha = 0.05, lfc = log2(1.2))
GGPlotly_Volcano(dep_EC_vs_E_pY, contrast = "EC_vs_E", add_names = TRUE, additional_title = "pY", proteins_of_interest = "EGFR")Return_DEP_Hits_Plots(data = pY_Set1_form, dep_EC_vs_E_pY, comparison = "EC_vs_E_diff")## 'select()' returned 1:1 mapping between keys and columns## 'select()' returned 1:many mapping between keys and columns## 'select()' returned 1:1 mapping between keys and columns
## pathway pval
## 1: A tetrasaccharide linker sequence is required for GAG synthesis 0.2920696
## 2: ABC transporter disorders 0.1566731
## 3: ABC-family proteins mediated transport 0.1566731
## 4: ADP signalling through P2Y purinoceptor 1 0.8142857
## 5: ALK mutants bind TKIs 0.1959184
## 6: APC/C-mediated degradation of cell cycle proteins 0.3647059
## padj log2err ES NES size leadingEdge
## 1: 0.7036232 0.10839426 -0.8430233 -1.1437044 1 6385
## 2: 0.6614330 0.15419097 -0.9127907 -1.2383558 1 5687
## 3: 0.6614330 0.15419097 -0.9127907 -1.2383558 1 5687
## 4: 0.9136051 0.05605959 0.5930233 0.7873775 1 1432
## 5: 0.6710708 0.14040624 0.9069767 1.2042244 1 1213
## 6: 0.7529467 0.10672988 -0.7251462 -1.1327565 2 5687,983#data_results <- get_df_long(dep)EBC vs EC
data_diff_EBC_vs_EC_pY <- test_diff(pY_se_Set1, type = "manual",
test = c("EBC_vs_EC"))## Tested contrasts: EBC_vs_ECdep_EBC_vs_EC_pY <- add_rejections_SH(data_diff_EBC_vs_EC_pY, alpha = 0.05, lfc = log2(1.2))
GGPlotly_Volcano(dep_EBC_vs_EC_pY, contrast = "EBC_vs_EC", add_names = TRUE, additional_title = "pY")Return_DEP_Hits_Plots(data = pY_Set1_form, dep_EBC_vs_EC_pY, comparison = "EBC_vs_EC_diff")## 'select()' returned 1:1 mapping between keys and columns## 'select()' returned 1:many mapping between keys and columns## 'select()' returned 1:1 mapping between keys and columns
## pathway pval
## 1: A tetrasaccharide linker sequence is required for GAG synthesis 0.1011673
## 2: ABC transporter disorders 0.9533074
## 3: ABC-family proteins mediated transport 0.9533074
## 4: ADP signalling through P2Y purinoceptor 1 0.1595331
## 5: ALK mutants bind TKIs 0.3385214
## 6: APC/C-mediated degradation of cell cycle proteins 0.8342541
## padj log2err ES NES size leadingEdge
## 1: 0.4384030 0.19578900 -0.9476744 -1.2667050 1 6385
## 2: 0.9754072 0.04660151 -0.5232558 -0.6994077 1 5687
## 3: 0.9754072 0.04660151 -0.5232558 -0.6994077 1 5687
## 4: 0.5845533 0.15315881 -0.9186047 -1.2278491 1 1432
## 5: 0.8158104 0.09957912 -0.8313953 -1.1112811 1 1213
## 6: 0.9754072 0.05019343 -0.5263158 -0.7832006 2 983,5687#data_results <- get_df_long(dep)Session Info
sessionInfo()## R version 4.1.3 (2022-03-10)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur/Monterey 10.16
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] forcats_0.5.2 stringr_1.4.1
## [3] dplyr_1.0.10 purrr_0.3.5
## [5] readr_2.1.3 tidyr_1.2.1
## [7] tibble_3.1.8 ggplot2_3.3.6
## [9] tidyverse_1.3.2 mdatools_0.13.0
## [11] SummarizedExperiment_1.24.0 GenomicRanges_1.46.1
## [13] GenomeInfoDb_1.30.1 MatrixGenerics_1.6.0
## [15] matrixStats_0.62.0 DEP_1.16.0
## [17] org.Hs.eg.db_3.14.0 AnnotationDbi_1.56.2
## [19] IRanges_2.28.0 S4Vectors_0.32.4
## [21] Biobase_2.54.0 BiocGenerics_0.40.0
## [23] fgsea_1.20.0
##
## loaded via a namespace (and not attached):
## [1] utf8_1.2.2 shinydashboard_0.7.2 proto_1.0.0
## [4] gmm_1.7 tidyselect_1.2.0 RSQLite_2.2.18
## [7] htmlwidgets_1.5.4 grid_4.1.3 BiocParallel_1.28.3
## [10] norm_1.0-10.0 munsell_0.5.0 codetools_0.2-18
## [13] preprocessCore_1.56.0 chron_2.3-58 DT_0.26
## [16] withr_2.5.0 colorspace_2.0-3 highr_0.9
## [19] knitr_1.40 rstudioapi_0.14 mzID_1.32.0
## [22] labeling_0.4.2 GenomeInfoDbData_1.2.7 bit64_4.0.5
## [25] farver_2.1.1 pheatmap_1.0.12 vctrs_0.5.0
## [28] generics_0.1.3 xfun_0.34 R6_2.5.1
## [31] doParallel_1.0.17 clue_0.3-62 MsCoreUtils_1.6.2
## [34] bitops_1.0-7 cachem_1.0.6 DelayedArray_0.20.0
## [37] assertthat_0.2.1 promises_1.2.0.1 scales_1.2.1
## [40] googlesheets4_1.0.1 gtable_0.3.1 affy_1.72.0
## [43] sandwich_3.0-2 rlang_1.0.6 mzR_2.28.0
## [46] GlobalOptions_0.1.2 lazyeval_0.2.2 gargle_1.2.1
## [49] impute_1.68.0 broom_1.0.1 BiocManager_1.30.19
## [52] yaml_2.3.6 modelr_0.1.9 crosstalk_1.2.0
## [55] backports_1.4.1 httpuv_1.6.6 tools_4.1.3
## [58] affyio_1.64.0 ellipsis_0.3.2 gplots_3.1.3
## [61] jquerylib_0.1.4 RColorBrewer_1.1-3 STRINGdb_2.6.5
## [64] MSnbase_2.20.4 gsubfn_0.7 Rcpp_1.0.9
## [67] hash_2.2.6.2 plyr_1.8.7 zlibbioc_1.40.0
## [70] RCurl_1.98-1.9 sqldf_0.4-11 GetoptLong_1.0.5
## [73] zoo_1.8-11 haven_2.5.1 cluster_2.1.4
## [76] fs_1.5.2 magrittr_2.0.3 data.table_1.14.4
## [79] circlize_0.4.15 reprex_2.0.2 reactome.db_1.77.0
## [82] googledrive_2.0.0 pcaMethods_1.86.0 mvtnorm_1.1-3
## [85] ProtGenerics_1.26.0 hms_1.1.2 mime_0.12
## [88] evaluate_0.17 xtable_1.8-4 XML_3.99-0.12
## [91] readxl_1.4.1 gridExtra_2.3 shape_1.4.6
## [94] compiler_4.1.3 KernSmooth_2.23-20 ncdf4_1.19
## [97] crayon_1.5.2 htmltools_0.5.3 later_1.3.0
## [100] tzdb_0.3.0 lubridate_1.8.0 DBI_1.1.3
## [103] dbplyr_2.2.1 ComplexHeatmap_2.10.0 MASS_7.3-58.1
## [106] tmvtnorm_1.5 Matrix_1.5-1 cli_3.4.1
## [109] vsn_3.62.0 imputeLCMD_2.1 parallel_4.1.3
## [112] igraph_1.3.5 pkgconfig_2.0.3 plotly_4.10.0
## [115] MALDIquant_1.21 xml2_1.3.3 foreach_1.5.2
## [118] bslib_0.4.0 XVector_0.34.0 rvest_1.0.3
## [121] digest_0.6.30 Biostrings_2.62.0 rmarkdown_2.17
## [124] cellranger_1.1.0 fastmatch_1.1-3 shiny_1.7.3
## [127] gtools_3.9.3 rjson_0.2.21 lifecycle_1.0.3
## [130] jsonlite_1.8.3 viridisLite_0.4.1 limma_3.50.3
## [133] fansi_1.0.3 pillar_1.8.1 lattice_0.20-45
## [136] KEGGREST_1.34.0 fastmap_1.1.0 httr_1.4.4
## [139] plotrix_3.8-2 glue_1.6.2 fdrtool_1.2.17
## [142] png_0.1-7 iterators_1.0.14 bit_4.0.4
## [145] stringi_1.7.8 sass_0.4.2 blob_1.2.3
## [148] caTools_1.18.2 memoise_2.0.1knitr::knit_exit()